Improvements On Personalized Search Engine Based On Multiple-pheromone Of Ant Colony Algorithm

With the high speed development of internet, network information is increasing and thestructure type is more and more complicated, this information are able to satisfy the requirementof various users. But it is impossible for our customers to search out the information they needamong the massive quantity. So before long of using the search engine, users find that it cannotsatisfy their individual requirement, search result contains much needless info. People hunger fora new engine with more intelligent, faster and more accurate which can meet all kinds ofdemands. Thus, the personalized engine arises.This article will firstly narrate the base and development status about the search engine andanalyze the feature of current general search engine and then lead to ontology search engine;ontology search engine is a profile to excavate personalized information of users. Second,describe how to build up ontology and solve the isomerization of ontology. Then in order tosolve the bottleneck of personalized searching, ant colony algorithm is brought in and cloudmodels are used to reform the ant colony algorithm to study it; Mainly introduce and studymulti-pheromone, conducting the strategy of personalized search by combining multi-pheromoneand ontology to increase efficiency of searching. Finally, experiment have achieved that thepersonalized search engine is differ from general one, compare their precision ratio and searchefficiency, having this conclusion: multi-pheromone ant colony algorithm of personalized searchengine is feasible.